Method Guides

Comprehensive tutorials on longitudinal analysis methods with simulated data examples.

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Growth Models

Model change trajectories over time using latent growth curves

Latent Growth Curve Models

Model individual trajectories over time using SEM-based growth curves.

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Mixed Models

Account for nested data structure with fixed and random effects

Linear Mixed Models

Model individual trajectories while accounting for the nested structure of longitudinal data.

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Coming Soon

Additional method guides in development

Coming Soon

Generalized Linear Mixed Models (GLMM)

Mixed-effects models for non-normal outcomes including binary, count, and categorical data.

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Generalized Estimating Equations (GEE)

Population-averaged models for correlated data with robust standard errors.

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Latent Change Score Models (LCS)

Structural equation models for examining true change over time while accounting for measurement error.